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"mode": "recorded",
"version": "1.5.1",
"recorded_on": "2026-10-11",
"examples": [
"What was the January invoice total?",
"Which evaluation metrics did the planning meeting agree to ship?",
"What does retrieval-augmented generation combine?"
],
"records": [
{
"question": "What was the January invoice total?",
"passages": [
{
"text": "The January 2025 invoice from Acme Corp totaled $1,240.50. File saved as `invoice-jan-2025.pdf` in Downloads.",
"source": "notes.md",
"score": 0.032522
},
{
"text": "PersonalRAGVault screenshot demo tasks:\n- Run ingest on this folder\n- Open UI at http://127.0.0.1:8501\n- Query: \"What was the January invoice total?\"\n- Show result cards and document preview",
"source": "todo.txt",
"score": 0.032522
},
{
"text": "We agreed to ship evaluation metrics (Hit@k, MRR, NDCG) and a Streamlit UI for browsing retrieval results.",
"source": "notes.md",
"score": 0.015873
}
],
"version": "1.5.1",
"generation": false,
"method": "MiniLM embeddings + hybrid retrieval",
"notice": "Matching passages can be irrelevant. Inspect the source; this is not a generated answer or a benchmark."
},
{
"question": "Which evaluation metrics did the planning meeting agree to ship?",
"passages": [
{
"text": "We agreed to ship evaluation metrics (Hit@k, MRR, NDCG) and a Streamlit UI for browsing retrieval results.",
"source": "notes.md",
"score": 0.032787
},
{
"text": "The January 2025 invoice from Acme Corp totaled $1,240.50. File saved as `invoice-jan-2025.pdf` in Downloads.",
"source": "notes.md",
"score": 0.032002
},
{
"text": "PersonalRAGVault screenshot demo tasks:\n- Run ingest on this folder\n- Open UI at http://127.0.0.1:8501\n- Query: \"What was the January invoice total?\"\n- Show result cards and document preview",
"source": "todo.txt",
"score": 0.031754
}
],
"version": "1.5.1",
"generation": false,
"method": "MiniLM embeddings + hybrid retrieval",
"notice": "Matching passages can be irrelevant. Inspect the source; this is not a generated answer or a benchmark."
},
{
"question": "What does retrieval-augmented generation combine?",
"passages": [
{
"text": "Retrieval-augmented generation combines vector search over your documents with a local LLM (Ollama) to answer questions using your own files.",
"source": "notes.md",
"score": 0.032787
},
{
"text": "We agreed to ship evaluation metrics (Hit@k, MRR, NDCG) and a Streamlit UI for browsing retrieval results.",
"source": "notes.md",
"score": 0.032002
},
{
"text": "PersonalRAGVault screenshot demo tasks:\n- Run ingest on this folder\n- Open UI at http://127.0.0.1:8501\n- Query: \"What was the January invoice total?\"\n- Show result cards and document preview",
"source": "todo.txt",
"score": 0.032002
}
],
"version": "1.5.1",
"generation": false,
"method": "MiniLM embeddings + hybrid retrieval",
"notice": "Matching passages can be irrelevant. Inspect the source; this is not a generated answer or a benchmark."
}
],
"sources": [
"notes.md",
"todo.txt"
],
"release": "https://github.com/seanebones-lang/personal-RAG/releases/tag/v1.5.1",
"corpus_sha256": {
"notes.md": "94b91e097b6a0b59cacc7624dd22a2a2cdad73eba5be744f83b58725145f8841",
"todo.txt": "72cea261e073944411fa6226e0d76a10a15df94ce8f4e51942c7ec1cdd5a0094"
}
}
|